Monthly Archives: November 2014

Instructions

In the text box at the top of the graph, enter the full name of a runner whose results can be found on UltraSignup, then hit enter.

The points on the graph represent individual race results for the given runner. Move your mouse over a point to see details of that race.

The line represents the evolution of the runner’s UltraSignup rank.

Timed events (eg, 12-hour races, 24-hour races) appear as empty circles. It seems that as of mid-October, 2014, timed events are included in the ranking. However, it is not clear to me if that change is retroactive, and in some circumstances, I cannot get my calculation of the ranking to line up with their calculation of the ranking. So if you have a large number of timed events in your history, the line I’ve calculated might be e’er so slightly off. The ranking reported below the graph is the official number, provided by UltraSignup.

Background

[Update: The friendly folks at UltraSignup came across this, and they liked it. I worked with them to get it integrated into the official runner results page. So now you can click the “History” link just below a runner’s overall score on UltraSignup and see the plot on the results page. Though if you like the spanky transitions between runners, you still need to come here.]

In the world of ultrarunning, it seems that the ranking calculated by UltraSignup has become the de facto standard for ranking runners. I think that part of the reason for its acceptance is its simplicity. A runner’s rank in a single race is just the ratio of the winner’s finish time to the runner’s finish time. So if you win a race, you get a 100%; if you take twice as long as the winner, you get a 50%. The overall ranking is a single number that represents an average of all of a given runner’s race rankings. If you were to look up my results on UltraSignup, you would see that as of this moment of this blog post, my 10+ years of racing ultras has been boiled down to a ranking of 88.43% over 48 races.

Of course, with simplicity comes inflexibility. What that number doesn’t capture is change over time. By summing up my results as a single number, it’s hard to see how my last few years of Lyme-impaired running have affected my rank, or how my (hoped-for) return to form will affect it. I was curious to see how runners progress over time, and how it affects the UltraSignup rank. In looking at the details of how UltraSignup delivers their rank pages, I noticed that the results come as JSON strings. Therefore, I realized, I wouldn’t even have to do any parsing of irregular data. I could just pull the JSON, and use my handy D3 skillz to put the results in a scatter plot.

I won’t go into great depth about implementation details. If you happen to be interested, you can go to the source. A passing familiarity with D3 would be helpful, but familiarity with only vanilla Javascript should allow you to get the gist.

Oh, and be aware that since this pulls data from UltraSignup, it’s entirely possible that it will stop working someday, either because they change the way they deliver data, or because they don’t like third parties creating mashups with their data. Also, this doesn’t work on Internet Explorer 8, or earlier. Sorry ’bout that!